commit files to HF hub
Browse files- all_results.json +8 -0
- best_configure.yaml +539 -0
- config.json +35 -0
- eval_results.json +8 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +1 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
all_results.json
ADDED
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@@ -0,0 +1,8 @@
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{
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"epoch": 2.0,
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"eval_accuracy": 0.9140625,
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"eval_loss": 0.4163683354854584,
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"eval_runtime": 7.4147,
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"eval_samples_per_second": 34.526,
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"eval_steps_per_second": 4.316
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}
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best_configure.yaml
ADDED
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@@ -0,0 +1,539 @@
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|
| 1 |
+
advance: null
|
| 2 |
+
approach: post_training_dynamic_quant
|
| 3 |
+
bf16_ops_list: []
|
| 4 |
+
calib_iteration: 1
|
| 5 |
+
calib_sampling_size: 100
|
| 6 |
+
framework: pytorch
|
| 7 |
+
op:
|
| 8 |
+
? !!python/tuple
|
| 9 |
+
- distilbert.transformer.layer.0.attention.q_lin
|
| 10 |
+
- Linear
|
| 11 |
+
: weight:
|
| 12 |
+
dtype: int8
|
| 13 |
+
scheme: sym
|
| 14 |
+
granularity: per_channel
|
| 15 |
+
algorithm: minmax
|
| 16 |
+
bit: 7.0
|
| 17 |
+
activation:
|
| 18 |
+
dtype: uint8
|
| 19 |
+
scheme: asym
|
| 20 |
+
granularity: per_tensor
|
| 21 |
+
algorithm: minmax
|
| 22 |
+
? !!python/tuple
|
| 23 |
+
- distilbert.transformer.layer.0.attention.k_lin
|
| 24 |
+
- Linear
|
| 25 |
+
: weight:
|
| 26 |
+
dtype: int8
|
| 27 |
+
scheme: sym
|
| 28 |
+
granularity: per_channel
|
| 29 |
+
algorithm: minmax
|
| 30 |
+
bit: 7.0
|
| 31 |
+
activation:
|
| 32 |
+
dtype: uint8
|
| 33 |
+
scheme: asym
|
| 34 |
+
granularity: per_tensor
|
| 35 |
+
algorithm: minmax
|
| 36 |
+
? !!python/tuple
|
| 37 |
+
- distilbert.transformer.layer.0.attention.v_lin
|
| 38 |
+
- Linear
|
| 39 |
+
: weight:
|
| 40 |
+
dtype: int8
|
| 41 |
+
scheme: sym
|
| 42 |
+
granularity: per_channel
|
| 43 |
+
algorithm: minmax
|
| 44 |
+
bit: 7.0
|
| 45 |
+
activation:
|
| 46 |
+
dtype: uint8
|
| 47 |
+
scheme: asym
|
| 48 |
+
granularity: per_tensor
|
| 49 |
+
algorithm: minmax
|
| 50 |
+
? !!python/tuple
|
| 51 |
+
- distilbert.transformer.layer.0.attention.out_lin
|
| 52 |
+
- Linear
|
| 53 |
+
: weight:
|
| 54 |
+
dtype: int8
|
| 55 |
+
scheme: sym
|
| 56 |
+
granularity: per_channel
|
| 57 |
+
algorithm: minmax
|
| 58 |
+
bit: 7.0
|
| 59 |
+
activation:
|
| 60 |
+
dtype: uint8
|
| 61 |
+
scheme: asym
|
| 62 |
+
granularity: per_tensor
|
| 63 |
+
algorithm: minmax
|
| 64 |
+
? !!python/tuple
|
| 65 |
+
- distilbert.transformer.layer.0.ffn.lin1
|
| 66 |
+
- Linear
|
| 67 |
+
: weight:
|
| 68 |
+
dtype: int8
|
| 69 |
+
scheme: sym
|
| 70 |
+
granularity: per_channel
|
| 71 |
+
algorithm: minmax
|
| 72 |
+
bit: 7.0
|
| 73 |
+
activation:
|
| 74 |
+
dtype: uint8
|
| 75 |
+
scheme: asym
|
| 76 |
+
granularity: per_tensor
|
| 77 |
+
algorithm: minmax
|
| 78 |
+
? !!python/tuple
|
| 79 |
+
- distilbert.transformer.layer.0.ffn.lin2
|
| 80 |
+
- Linear
|
| 81 |
+
: weight:
|
| 82 |
+
dtype: int8
|
| 83 |
+
scheme: sym
|
| 84 |
+
granularity: per_channel
|
| 85 |
+
algorithm: minmax
|
| 86 |
+
bit: 7.0
|
| 87 |
+
activation:
|
| 88 |
+
dtype: uint8
|
| 89 |
+
scheme: asym
|
| 90 |
+
granularity: per_tensor
|
| 91 |
+
algorithm: minmax
|
| 92 |
+
? !!python/tuple
|
| 93 |
+
- distilbert.transformer.layer.1.attention.q_lin
|
| 94 |
+
- Linear
|
| 95 |
+
: weight:
|
| 96 |
+
dtype: int8
|
| 97 |
+
scheme: sym
|
| 98 |
+
granularity: per_channel
|
| 99 |
+
algorithm: minmax
|
| 100 |
+
bit: 7.0
|
| 101 |
+
activation:
|
| 102 |
+
dtype: uint8
|
| 103 |
+
scheme: asym
|
| 104 |
+
granularity: per_tensor
|
| 105 |
+
algorithm: minmax
|
| 106 |
+
? !!python/tuple
|
| 107 |
+
- distilbert.transformer.layer.1.attention.k_lin
|
| 108 |
+
- Linear
|
| 109 |
+
: weight:
|
| 110 |
+
dtype: int8
|
| 111 |
+
scheme: sym
|
| 112 |
+
granularity: per_channel
|
| 113 |
+
algorithm: minmax
|
| 114 |
+
bit: 7.0
|
| 115 |
+
activation:
|
| 116 |
+
dtype: uint8
|
| 117 |
+
scheme: asym
|
| 118 |
+
granularity: per_tensor
|
| 119 |
+
algorithm: minmax
|
| 120 |
+
? !!python/tuple
|
| 121 |
+
- distilbert.transformer.layer.1.attention.v_lin
|
| 122 |
+
- Linear
|
| 123 |
+
: weight:
|
| 124 |
+
dtype: int8
|
| 125 |
+
scheme: sym
|
| 126 |
+
granularity: per_channel
|
| 127 |
+
algorithm: minmax
|
| 128 |
+
bit: 7.0
|
| 129 |
+
activation:
|
| 130 |
+
dtype: uint8
|
| 131 |
+
scheme: asym
|
| 132 |
+
granularity: per_tensor
|
| 133 |
+
algorithm: minmax
|
| 134 |
+
? !!python/tuple
|
| 135 |
+
- distilbert.transformer.layer.1.attention.out_lin
|
| 136 |
+
- Linear
|
| 137 |
+
: weight:
|
| 138 |
+
dtype: int8
|
| 139 |
+
scheme: sym
|
| 140 |
+
granularity: per_channel
|
| 141 |
+
algorithm: minmax
|
| 142 |
+
bit: 7.0
|
| 143 |
+
activation:
|
| 144 |
+
dtype: uint8
|
| 145 |
+
scheme: asym
|
| 146 |
+
granularity: per_tensor
|
| 147 |
+
algorithm: minmax
|
| 148 |
+
? !!python/tuple
|
| 149 |
+
- distilbert.transformer.layer.1.ffn.lin1
|
| 150 |
+
- Linear
|
| 151 |
+
: weight:
|
| 152 |
+
dtype: int8
|
| 153 |
+
scheme: sym
|
| 154 |
+
granularity: per_channel
|
| 155 |
+
algorithm: minmax
|
| 156 |
+
bit: 7.0
|
| 157 |
+
activation:
|
| 158 |
+
dtype: uint8
|
| 159 |
+
scheme: asym
|
| 160 |
+
granularity: per_tensor
|
| 161 |
+
algorithm: minmax
|
| 162 |
+
? !!python/tuple
|
| 163 |
+
- distilbert.transformer.layer.1.ffn.lin2
|
| 164 |
+
- Linear
|
| 165 |
+
: weight:
|
| 166 |
+
dtype: int8
|
| 167 |
+
scheme: sym
|
| 168 |
+
granularity: per_channel
|
| 169 |
+
algorithm: minmax
|
| 170 |
+
bit: 7.0
|
| 171 |
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activation:
|
| 172 |
+
dtype: uint8
|
| 173 |
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scheme: asym
|
| 174 |
+
granularity: per_tensor
|
| 175 |
+
algorithm: minmax
|
| 176 |
+
? !!python/tuple
|
| 177 |
+
- distilbert.transformer.layer.2.attention.q_lin
|
| 178 |
+
- Linear
|
| 179 |
+
: weight:
|
| 180 |
+
dtype: int8
|
| 181 |
+
scheme: sym
|
| 182 |
+
granularity: per_channel
|
| 183 |
+
algorithm: minmax
|
| 184 |
+
bit: 7.0
|
| 185 |
+
activation:
|
| 186 |
+
dtype: uint8
|
| 187 |
+
scheme: asym
|
| 188 |
+
granularity: per_tensor
|
| 189 |
+
algorithm: minmax
|
| 190 |
+
? !!python/tuple
|
| 191 |
+
- distilbert.transformer.layer.2.attention.k_lin
|
| 192 |
+
- Linear
|
| 193 |
+
: weight:
|
| 194 |
+
dtype: int8
|
| 195 |
+
scheme: sym
|
| 196 |
+
granularity: per_channel
|
| 197 |
+
algorithm: minmax
|
| 198 |
+
bit: 7.0
|
| 199 |
+
activation:
|
| 200 |
+
dtype: uint8
|
| 201 |
+
scheme: asym
|
| 202 |
+
granularity: per_tensor
|
| 203 |
+
algorithm: minmax
|
| 204 |
+
? !!python/tuple
|
| 205 |
+
- distilbert.transformer.layer.2.attention.v_lin
|
| 206 |
+
- Linear
|
| 207 |
+
: weight:
|
| 208 |
+
dtype: int8
|
| 209 |
+
scheme: sym
|
| 210 |
+
granularity: per_channel
|
| 211 |
+
algorithm: minmax
|
| 212 |
+
bit: 7.0
|
| 213 |
+
activation:
|
| 214 |
+
dtype: uint8
|
| 215 |
+
scheme: asym
|
| 216 |
+
granularity: per_tensor
|
| 217 |
+
algorithm: minmax
|
| 218 |
+
? !!python/tuple
|
| 219 |
+
- distilbert.transformer.layer.2.attention.out_lin
|
| 220 |
+
- Linear
|
| 221 |
+
: weight:
|
| 222 |
+
dtype: int8
|
| 223 |
+
scheme: sym
|
| 224 |
+
granularity: per_channel
|
| 225 |
+
algorithm: minmax
|
| 226 |
+
bit: 7.0
|
| 227 |
+
activation:
|
| 228 |
+
dtype: uint8
|
| 229 |
+
scheme: asym
|
| 230 |
+
granularity: per_tensor
|
| 231 |
+
algorithm: minmax
|
| 232 |
+
? !!python/tuple
|
| 233 |
+
- distilbert.transformer.layer.2.ffn.lin1
|
| 234 |
+
- Linear
|
| 235 |
+
: weight:
|
| 236 |
+
dtype: int8
|
| 237 |
+
scheme: sym
|
| 238 |
+
granularity: per_channel
|
| 239 |
+
algorithm: minmax
|
| 240 |
+
bit: 7.0
|
| 241 |
+
activation:
|
| 242 |
+
dtype: uint8
|
| 243 |
+
scheme: asym
|
| 244 |
+
granularity: per_tensor
|
| 245 |
+
algorithm: minmax
|
| 246 |
+
? !!python/tuple
|
| 247 |
+
- distilbert.transformer.layer.2.ffn.lin2
|
| 248 |
+
- Linear
|
| 249 |
+
: weight:
|
| 250 |
+
dtype: int8
|
| 251 |
+
scheme: sym
|
| 252 |
+
granularity: per_channel
|
| 253 |
+
algorithm: minmax
|
| 254 |
+
bit: 7.0
|
| 255 |
+
activation:
|
| 256 |
+
dtype: uint8
|
| 257 |
+
scheme: asym
|
| 258 |
+
granularity: per_tensor
|
| 259 |
+
algorithm: minmax
|
| 260 |
+
? !!python/tuple
|
| 261 |
+
- distilbert.transformer.layer.3.attention.q_lin
|
| 262 |
+
- Linear
|
| 263 |
+
: weight:
|
| 264 |
+
dtype: int8
|
| 265 |
+
scheme: sym
|
| 266 |
+
granularity: per_channel
|
| 267 |
+
algorithm: minmax
|
| 268 |
+
bit: 7.0
|
| 269 |
+
activation:
|
| 270 |
+
dtype: uint8
|
| 271 |
+
scheme: asym
|
| 272 |
+
granularity: per_tensor
|
| 273 |
+
algorithm: minmax
|
| 274 |
+
? !!python/tuple
|
| 275 |
+
- distilbert.transformer.layer.3.attention.k_lin
|
| 276 |
+
- Linear
|
| 277 |
+
: weight:
|
| 278 |
+
dtype: int8
|
| 279 |
+
scheme: sym
|
| 280 |
+
granularity: per_channel
|
| 281 |
+
algorithm: minmax
|
| 282 |
+
bit: 7.0
|
| 283 |
+
activation:
|
| 284 |
+
dtype: uint8
|
| 285 |
+
scheme: asym
|
| 286 |
+
granularity: per_tensor
|
| 287 |
+
algorithm: minmax
|
| 288 |
+
? !!python/tuple
|
| 289 |
+
- distilbert.transformer.layer.3.attention.v_lin
|
| 290 |
+
- Linear
|
| 291 |
+
: weight:
|
| 292 |
+
dtype: int8
|
| 293 |
+
scheme: sym
|
| 294 |
+
granularity: per_channel
|
| 295 |
+
algorithm: minmax
|
| 296 |
+
bit: 7.0
|
| 297 |
+
activation:
|
| 298 |
+
dtype: uint8
|
| 299 |
+
scheme: asym
|
| 300 |
+
granularity: per_tensor
|
| 301 |
+
algorithm: minmax
|
| 302 |
+
? !!python/tuple
|
| 303 |
+
- distilbert.transformer.layer.3.attention.out_lin
|
| 304 |
+
- Linear
|
| 305 |
+
: weight:
|
| 306 |
+
dtype: int8
|
| 307 |
+
scheme: sym
|
| 308 |
+
granularity: per_channel
|
| 309 |
+
algorithm: minmax
|
| 310 |
+
bit: 7.0
|
| 311 |
+
activation:
|
| 312 |
+
dtype: uint8
|
| 313 |
+
scheme: asym
|
| 314 |
+
granularity: per_tensor
|
| 315 |
+
algorithm: minmax
|
| 316 |
+
? !!python/tuple
|
| 317 |
+
- distilbert.transformer.layer.3.ffn.lin1
|
| 318 |
+
- Linear
|
| 319 |
+
: weight:
|
| 320 |
+
dtype: int8
|
| 321 |
+
scheme: sym
|
| 322 |
+
granularity: per_channel
|
| 323 |
+
algorithm: minmax
|
| 324 |
+
bit: 7.0
|
| 325 |
+
activation:
|
| 326 |
+
dtype: uint8
|
| 327 |
+
scheme: asym
|
| 328 |
+
granularity: per_tensor
|
| 329 |
+
algorithm: minmax
|
| 330 |
+
? !!python/tuple
|
| 331 |
+
- distilbert.transformer.layer.3.ffn.lin2
|
| 332 |
+
- Linear
|
| 333 |
+
: weight:
|
| 334 |
+
dtype: int8
|
| 335 |
+
scheme: sym
|
| 336 |
+
granularity: per_channel
|
| 337 |
+
algorithm: minmax
|
| 338 |
+
bit: 7.0
|
| 339 |
+
activation:
|
| 340 |
+
dtype: uint8
|
| 341 |
+
scheme: asym
|
| 342 |
+
granularity: per_tensor
|
| 343 |
+
algorithm: minmax
|
| 344 |
+
? !!python/tuple
|
| 345 |
+
- distilbert.transformer.layer.4.attention.q_lin
|
| 346 |
+
- Linear
|
| 347 |
+
: weight:
|
| 348 |
+
dtype: int8
|
| 349 |
+
scheme: sym
|
| 350 |
+
granularity: per_channel
|
| 351 |
+
algorithm: minmax
|
| 352 |
+
bit: 7.0
|
| 353 |
+
activation:
|
| 354 |
+
dtype: uint8
|
| 355 |
+
scheme: asym
|
| 356 |
+
granularity: per_tensor
|
| 357 |
+
algorithm: minmax
|
| 358 |
+
? !!python/tuple
|
| 359 |
+
- distilbert.transformer.layer.4.attention.k_lin
|
| 360 |
+
- Linear
|
| 361 |
+
: weight:
|
| 362 |
+
dtype: int8
|
| 363 |
+
scheme: sym
|
| 364 |
+
granularity: per_channel
|
| 365 |
+
algorithm: minmax
|
| 366 |
+
bit: 7.0
|
| 367 |
+
activation:
|
| 368 |
+
dtype: uint8
|
| 369 |
+
scheme: asym
|
| 370 |
+
granularity: per_tensor
|
| 371 |
+
algorithm: minmax
|
| 372 |
+
? !!python/tuple
|
| 373 |
+
- distilbert.transformer.layer.4.attention.v_lin
|
| 374 |
+
- Linear
|
| 375 |
+
: weight:
|
| 376 |
+
dtype: int8
|
| 377 |
+
scheme: sym
|
| 378 |
+
granularity: per_channel
|
| 379 |
+
algorithm: minmax
|
| 380 |
+
bit: 7.0
|
| 381 |
+
activation:
|
| 382 |
+
dtype: uint8
|
| 383 |
+
scheme: asym
|
| 384 |
+
granularity: per_tensor
|
| 385 |
+
algorithm: minmax
|
| 386 |
+
? !!python/tuple
|
| 387 |
+
- distilbert.transformer.layer.4.attention.out_lin
|
| 388 |
+
- Linear
|
| 389 |
+
: weight:
|
| 390 |
+
dtype: int8
|
| 391 |
+
scheme: sym
|
| 392 |
+
granularity: per_channel
|
| 393 |
+
algorithm: minmax
|
| 394 |
+
bit: 7.0
|
| 395 |
+
activation:
|
| 396 |
+
dtype: uint8
|
| 397 |
+
scheme: asym
|
| 398 |
+
granularity: per_tensor
|
| 399 |
+
algorithm: minmax
|
| 400 |
+
? !!python/tuple
|
| 401 |
+
- distilbert.transformer.layer.4.ffn.lin1
|
| 402 |
+
- Linear
|
| 403 |
+
: weight:
|
| 404 |
+
dtype: int8
|
| 405 |
+
scheme: sym
|
| 406 |
+
granularity: per_channel
|
| 407 |
+
algorithm: minmax
|
| 408 |
+
bit: 7.0
|
| 409 |
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activation:
|
| 410 |
+
dtype: uint8
|
| 411 |
+
scheme: asym
|
| 412 |
+
granularity: per_tensor
|
| 413 |
+
algorithm: minmax
|
| 414 |
+
? !!python/tuple
|
| 415 |
+
- distilbert.transformer.layer.4.ffn.lin2
|
| 416 |
+
- Linear
|
| 417 |
+
: weight:
|
| 418 |
+
dtype: int8
|
| 419 |
+
scheme: sym
|
| 420 |
+
granularity: per_channel
|
| 421 |
+
algorithm: minmax
|
| 422 |
+
bit: 7.0
|
| 423 |
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activation:
|
| 424 |
+
dtype: uint8
|
| 425 |
+
scheme: asym
|
| 426 |
+
granularity: per_tensor
|
| 427 |
+
algorithm: minmax
|
| 428 |
+
? !!python/tuple
|
| 429 |
+
- distilbert.transformer.layer.5.attention.q_lin
|
| 430 |
+
- Linear
|
| 431 |
+
: weight:
|
| 432 |
+
dtype: int8
|
| 433 |
+
scheme: sym
|
| 434 |
+
granularity: per_channel
|
| 435 |
+
algorithm: minmax
|
| 436 |
+
bit: 7.0
|
| 437 |
+
activation:
|
| 438 |
+
dtype: uint8
|
| 439 |
+
scheme: asym
|
| 440 |
+
granularity: per_tensor
|
| 441 |
+
algorithm: minmax
|
| 442 |
+
? !!python/tuple
|
| 443 |
+
- distilbert.transformer.layer.5.attention.k_lin
|
| 444 |
+
- Linear
|
| 445 |
+
: weight:
|
| 446 |
+
dtype: int8
|
| 447 |
+
scheme: sym
|
| 448 |
+
granularity: per_channel
|
| 449 |
+
algorithm: minmax
|
| 450 |
+
bit: 7.0
|
| 451 |
+
activation:
|
| 452 |
+
dtype: uint8
|
| 453 |
+
scheme: asym
|
| 454 |
+
granularity: per_tensor
|
| 455 |
+
algorithm: minmax
|
| 456 |
+
? !!python/tuple
|
| 457 |
+
- distilbert.transformer.layer.5.attention.v_lin
|
| 458 |
+
- Linear
|
| 459 |
+
: weight:
|
| 460 |
+
dtype: int8
|
| 461 |
+
scheme: sym
|
| 462 |
+
granularity: per_channel
|
| 463 |
+
algorithm: minmax
|
| 464 |
+
bit: 7.0
|
| 465 |
+
activation:
|
| 466 |
+
dtype: uint8
|
| 467 |
+
scheme: asym
|
| 468 |
+
granularity: per_tensor
|
| 469 |
+
algorithm: minmax
|
| 470 |
+
? !!python/tuple
|
| 471 |
+
- distilbert.transformer.layer.5.attention.out_lin
|
| 472 |
+
- Linear
|
| 473 |
+
: weight:
|
| 474 |
+
dtype: int8
|
| 475 |
+
scheme: sym
|
| 476 |
+
granularity: per_channel
|
| 477 |
+
algorithm: minmax
|
| 478 |
+
bit: 7.0
|
| 479 |
+
activation:
|
| 480 |
+
dtype: uint8
|
| 481 |
+
scheme: asym
|
| 482 |
+
granularity: per_tensor
|
| 483 |
+
algorithm: minmax
|
| 484 |
+
? !!python/tuple
|
| 485 |
+
- distilbert.transformer.layer.5.ffn.lin1
|
| 486 |
+
- Linear
|
| 487 |
+
: weight:
|
| 488 |
+
dtype: int8
|
| 489 |
+
scheme: sym
|
| 490 |
+
granularity: per_channel
|
| 491 |
+
algorithm: minmax
|
| 492 |
+
bit: 7.0
|
| 493 |
+
activation:
|
| 494 |
+
dtype: uint8
|
| 495 |
+
scheme: asym
|
| 496 |
+
granularity: per_tensor
|
| 497 |
+
algorithm: minmax
|
| 498 |
+
? !!python/tuple
|
| 499 |
+
- distilbert.transformer.layer.5.ffn.lin2
|
| 500 |
+
- Linear
|
| 501 |
+
: weight:
|
| 502 |
+
dtype: int8
|
| 503 |
+
scheme: sym
|
| 504 |
+
granularity: per_channel
|
| 505 |
+
algorithm: minmax
|
| 506 |
+
bit: 7.0
|
| 507 |
+
activation:
|
| 508 |
+
dtype: uint8
|
| 509 |
+
scheme: asym
|
| 510 |
+
granularity: per_tensor
|
| 511 |
+
algorithm: minmax
|
| 512 |
+
? !!python/tuple
|
| 513 |
+
- pre_classifier
|
| 514 |
+
- Linear
|
| 515 |
+
: weight:
|
| 516 |
+
dtype: int8
|
| 517 |
+
scheme: sym
|
| 518 |
+
granularity: per_channel
|
| 519 |
+
algorithm: minmax
|
| 520 |
+
bit: 7.0
|
| 521 |
+
activation:
|
| 522 |
+
dtype: uint8
|
| 523 |
+
scheme: asym
|
| 524 |
+
granularity: per_tensor
|
| 525 |
+
algorithm: minmax
|
| 526 |
+
? !!python/tuple
|
| 527 |
+
- classifier
|
| 528 |
+
- Linear
|
| 529 |
+
: weight:
|
| 530 |
+
dtype: int8
|
| 531 |
+
scheme: sym
|
| 532 |
+
granularity: per_channel
|
| 533 |
+
algorithm: minmax
|
| 534 |
+
bit: 7.0
|
| 535 |
+
activation:
|
| 536 |
+
dtype: uint8
|
| 537 |
+
scheme: asym
|
| 538 |
+
granularity: per_tensor
|
| 539 |
+
algorithm: minmax
|
config.json
ADDED
|
@@ -0,0 +1,35 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_name_or_path": "distilbert-base-uncased-finetuned-sst-2-english",
|
| 3 |
+
"activation": "gelu",
|
| 4 |
+
"architectures": [
|
| 5 |
+
"DistilBertForSequenceClassification"
|
| 6 |
+
],
|
| 7 |
+
"attention_dropout": 0.1,
|
| 8 |
+
"dim": 768,
|
| 9 |
+
"dropout": 0.1,
|
| 10 |
+
"finetuning_task": "sst-2",
|
| 11 |
+
"hidden_dim": 3072,
|
| 12 |
+
"id2label": {
|
| 13 |
+
"0": "NEGATIVE",
|
| 14 |
+
"1": "POSITIVE"
|
| 15 |
+
},
|
| 16 |
+
"initializer_range": 0.02,
|
| 17 |
+
"label2id": {
|
| 18 |
+
"NEGATIVE": 0,
|
| 19 |
+
"POSITIVE": 1
|
| 20 |
+
},
|
| 21 |
+
"max_position_embeddings": 512,
|
| 22 |
+
"model_type": "distilbert",
|
| 23 |
+
"n_heads": 12,
|
| 24 |
+
"n_layers": 6,
|
| 25 |
+
"output_past": true,
|
| 26 |
+
"pad_token_id": 0,
|
| 27 |
+
"problem_type": "single_label_classification",
|
| 28 |
+
"qa_dropout": 0.1,
|
| 29 |
+
"seq_classif_dropout": 0.2,
|
| 30 |
+
"sinusoidal_pos_embds": false,
|
| 31 |
+
"tie_weights_": true,
|
| 32 |
+
"torch_dtype": "float32",
|
| 33 |
+
"transformers_version": "4.16.2",
|
| 34 |
+
"vocab_size": 30522
|
| 35 |
+
}
|
eval_results.json
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"epoch": 2.0,
|
| 3 |
+
"eval_accuracy": 0.9140625,
|
| 4 |
+
"eval_loss": 0.4163683354854584,
|
| 5 |
+
"eval_runtime": 7.4147,
|
| 6 |
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"eval_samples_per_second": 34.526,
|
| 7 |
+
"eval_steps_per_second": 4.316
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| 8 |
+
}
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pytorch_model.bin
ADDED
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| 1 |
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version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5c26bbb1c8fe2e14ebb47bb01a181fbecbc9be9701eebca44aa7aa59af26fa0d
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| 3 |
+
size 139407425
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special_tokens_map.json
ADDED
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| 1 |
+
{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
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tokenizer.json
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tokenizer_config.json
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| 1 |
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{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "distilbert-base-uncased-finetuned-sst-2-english", "do_basic_tokenize": true, "never_split": null, "tokenizer_class": "DistilBertTokenizer"}
|
training_args.bin
ADDED
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|
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|
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|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:517b5da8c631bd38130817f6712c8388a1c2674d4b6c2214a2d0ba5cd8999187
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| 3 |
+
size 2991
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vocab.txt
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